Topic
Transfer function
About: Transfer function is a research topic. Over the lifetime, 14362 publications have been published within this topic receiving 214983 citations. The topic is also known as: system function & network function.
Papers published on a yearly basis
Papers
More filters
Patent•
28 Aug 1991TL;DR: In this article, a reconstruction filter is used to recover the original input signals from decorrelated source signals, such that the cross-correlation between the reconstructed source signals is near zero, and the transfer functions which represent the crosstalk processes are estimated.
Abstract: A system separates unknown signals which have been combined together through unknown linear filters and for which observations at multiple sensors are made. In a two channel circuit with two inputs and two sensors, the reconstructed source signals are assumed to be decorrelated such that the cross-correlation between the reconstructed source signals is near zero. The transfer functions which represent the crosstalk processes are estimated. The output signals are detected and the transfer functions are recursively solved. A reconstruction filter is used to recover the original input signals.
51 citations
Book•
01 Aug 2002
TL;DR: The z Transform and Its Properties are compared to Solving Linear Differential Equation and Eigenvalues in Digital Signal Processing, which is a very simple and straightforward way to model the dynamic response of a discrete-time system.
Abstract: Preface. 1. Introduction to Linear Systems. 1.1 Continuous and Discrete Linear Systems and Signals. 1.2 System Linearity and Time Invariance. 1.3 Mathematical Modeling of Systems. 1.4 System Classification. 1.5 MATLAB System Computer Analysis and Design. 1.6 Book Organization. 1.7 Chapter One Summary. 1.8 References. 1.9 Problems. 2. Introduction to Signals. 2.1 Common Signals in Linear Systems. 2.2 Signal Operations. 2.3 Signal Classification. 2.4 MATLAB Laboratory Experiment on Signals. 2.5 Chapter Two Summary. 2.6 References. 2.7 Problems. I. FREQUENCY DOMAIN TECHNIQUES. 3. Fourier Series and Fourier Transform. 3.1 Fourier Series. 3.2 Fourier Transform and Its Properties. 3.3 Fourier Transform in System Analysis. 3.4 Fourier Series in Systems Analysis. 3.5 From Fourier Transform to Laplace Transform. 3.6 Fourier Analysis MATLAB Laboratory Experiment. 3.7 Chapter Three Summary. 3.8 References. 3.9 Problems. 4. Laplace Transform. 4.1 Laplace Transform and Its Properties. 4.2 Inverse Laplace Transform. 4.3 Laplace Transform in Linear System Analysis. 4.4 Block Diagrams. 4.5 From Laplace to the z-Transform. 4.6 MATLAB Laboratory Experiment. 4.7 Chapter Four Summary. 4.8 References. 4.9 Problems. 5. The z Transform. 5.1 The z Transform and Its Properties. 5.2 Inverse of the z Transform. 5.3 The z Transform in Linear System Analysis. 5.4 Block Diagram. 5.5 Discrete-Time Frequency Spectra. 5.6 MATLAB Laboratory Experiment. 5.7 Chapter Five Summary. 5.8 References. 5.9 Problems. II. TIME DOMAIN TECHNIQUES. 6. Convolution. 6.1 Convolution of Continuous-Time Signals. 6.2 Convolution for Linear Continuous-Time Systems. 6.3 Convolution of Discrete-Time Signals. 6.4 Convolution for Linear Discrete-Time Systems. 6.5 Numerical Convolution Using MATLAB. 6.6 MATLAB Laboratory Experiments on Convolution. 6.7 Chapter Six Summary. 6.8 References. 6.9 Problems. 7. System Response in Time Domain. 7.1 Solving Linear Differential Equations. 7.2 Solving Linear Difference Equations. 7.3 Discrete-Time System Impulse Response. 7.4 Continuous-Time System Impulse Response. 7.5 Complete Continuous-Time System Response. 7.6 Complete Discrete-Time System Response. 7.7 Stability of Continuous-Time Linear Systems. 7.8 Stability of Discrete-Time Linear Systems. 7.9 MATLAB Experiment on Continuous-Time Systems. 7.10 MATLAB Experiment on Discrete-Time Systems. 7.11 Chapter Seven Summary. 7.12 References. 7.13 Problems. 8. State Space Approach. 8.1 State Space Models. 8.2 Time Response from the State Equation. 8.3 Discrete-Time Models. 8.4 System Characteristic Equation and Eigenvalues. 8.5 Cayley-Hamilton Theorem. 8.6 Linearization of Nonlinear System. 8.7 State Space MATLAB Laboratory Experiments. 8.8 Chapter Eight Summary. 8.9 References. 8.10 Problems. III. SYSTEMS IN ELECTRICAL ENGINEERING. 9. Signals in Digital Signal Processing. 9.1 Sampling Theorem. 9.2 Discrete-Time Fourier Transform (DFDT). 9.3 Double Sided z-Transform. 9.4 Discrete Fourier Transform. 9.5 Discrete-Time Fourier Series. 9.6 Correlation of Discrete-Time Signals. 9.7 FIR and IIR Filters. 9.8 Laboratory Experiment on Digital Signal Processing. 9.9 Chapter Nine Summary. 9.10 References. 9.11 Problems. 10. Signals in Communication Systems. 10.1 Signal Transmission in Communications. 10.2 Signal Correlation, Energy and Power Spectra. 10.3 Hilbert Transform. 10.4 Ideal Filter. 10.5 Modulation and Demodulation. 10.6 Digital Communication System. 10.7 Communication Systems Laboratory Experiment. 10.8 Chapter Ten Summary. 10.9 References. 10.10 Problems. 11. Linear Electric Circuits. 11.1 Basic Relations. 11.2 First-Order Linear Electrical Circuits. 11.3 Second-Order Linear Electrical Circuits. 11.4 Higher-Order Linear Electrical Circuits. 11.5 Chapter Eleven Summary. 11.6 References. 11.7 MATLAB Laboratory Experiment. 11.8 Problems. 12. Linear Controls Systems. 12.1 The Essence of Feedback. 12.2 Transient Response of Second-Order Systems. 12.3 Feedback System Steady State Errors. 12.4 Feedback System Frequency Characteristics. 12.5 Bode Diagrams. 12.6 Common Dynamic Controllers: PD, PI, PID. 12.7 Laboratory Experiment on Control Systems. 12.8 Chapter Twelve Summary. 12.9 References. 12.10 Problems. Appendices. A. Linear Algebra. B. Some Results from Calculus. C. Introduction to MATLAB. D. Introduction to SIMULINK. Index.
51 citations
TL;DR: In this paper, a generalized predictive control strategy with novel parameter identification method from step test for multiple inputs and multiple outputs (MIMO) systems is presented, where the coupled closed loop MIMO system is decoupled equivalently into four individual single open loop processes with the same input signal acting on the four transfer functions.
51 citations
01 Jul 1978
TL;DR: In this article, it was shown that the double bilinear transformation approach for designing a 2D IIR digital transfer function from a predetermined 2D analog transfer function may in certain cases lead to unstable solutions.
Abstract: It is shown that the double bilinear transformation approach for designing a 2-D IIR digital transfer function from a predetermined 2-D analog transfer function, may in certain cases lead to unstable solutions.
51 citations